1. Field
The present disclosure relates generally to search engine content management systems, and, more particularly, to a machine for recognizing or generating Jabba-type sequences for use in or with search engine content management systems.
2. Information
The Internet is widespread. The World Wide Web or simply the Web, provided by the Internet, is growing rapidly, at least in part, from the large amount of content being added seemingly on a daily basis. A wide variety of content, such as one or more electronic documents, for example, is continually being identified, located, retrieved, accumulated, stored, or communicated. Various information databases including, for example, knowledge bases or other collections of content, Web-based or otherwise, have become commonplace, as have related communication networks or computing resources that help users to access relevant information. Effectively or efficiently identifying or locating content of interest may facilitate or support information-seeking behavior of users and may lead to an increased usability of a search engine.
With a large amount of content being available, a number of tools may often be provided to allow for copious amounts of information to be searched through in an efficient or effective manner. For example, service providers may allow users to search the Web or other networks, databases or like data repositories using search engines. In some instances, to facilitate or support one or more processes or operations of a search engine, a finite state machine (FSM) may, for example, be employed. An FSM may typically refer to a model of behavior comprising a finite number of states, transitions between states, as well as associated outputs or actions. In some instances, an FSM may be represented via a suitable data structure, such as a graph, for example, with vertices corresponding to states of an FSM, and edges corresponding to transitions between FSM states due to one or more inputs. A search engine-related application of an FSM may include, for example, text processing or matching, in which the machine may function as a sequence recognizer. At times, however, a number of possible sequences to be matched for a given input may grow relatively large due, at least in part, to a number of repetitive or unnecessary graph traversals, which may make matching tasks more labor-intensive or error-prone.